DSA 469 - Big Data Processing Systems

[3 credit(s)]

Prerequisites: CIS 430. Detailed study of modern database processing and parallel database processing systems for big data processing. The topics include Transaction concept, concurrency control strategies, semistructured and unstructured data processing strategies. The course advances the study with big data processing strategies on distributed file system Hadoop with Map Reduce paradigm and focuses on the study of massively parallel database processing systems for big data processing with selective NoSQL systems, NewSQL systems, and cloud computing platforms and infrastructures. The course covers data model, index, querying techniques, data processing methods, and ACID (Atomicity, Consistency, Isolation, and Durability) issues in parallel database processing systems. The students will get hands-on experiences on big data processing systems with processing real time big data stream obtained from well-known social network sites. Finally, the course will explore the latest advances in industry research for big data processing and data analytics.

Semesters Offered: Every Fall and Spring

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